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Nova · Professor Researcher · re-ranking top 20…
Deepak Ganesan

Deepak Ganesan

University of Massachusetts Amherst · Epidemiology

Active 2001–2024

h-index50
Citations11.8k
Papers21575 last 5y
Funding$52.4M1 active
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Research topics

  • Computer Science
  • Artificial Intelligence
  • Embedded system
  • Telecommunications
  • Optics
  • Operating system
  • Data science
  • Human–computer interaction
  • Computer vision
  • Computer architecture

Selected publications

  • Multimodal Smart Eyewear for Longitudinal Eye Movement Tracking

    Matter · 2020 · 55 citations

    • Computer Science
    • Artificial Intelligence
    • Computer Science
  • CLIO

    Proceedings of the 28th Annual International Conference on Mobile Computing And Networking · 2020 · 67 citations

    • Computer Science
    • Artificial Intelligence
    • Computer Science

    Recent years have seen dramatic advances in low-power neural accelerators that aim to bring deep learning analytics to IoT devices; simultaneously, there have been considerable advances in the design of low-power radios to enable efficient compute offload from IoT devices to the cloud. Neither is a panacea --- deep learning models are often too large for low-power accelerators and bandwidth needs are often too high for low-power radios. While there has been considerable work on deep learning for smartphone-class devices, these methods do not work well for small battery-powered IoT devices that are considerably more resource-constrained.

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